The present disclosure relates to an imaging system including an imaging device and a reconstruction device configured to reconstruct an image using a signal transmitted from the imaging device.
In recent years, there have been widely spread techniques in which an imaging device is mounted on a household appliance, such as a TV, an air conditioner, a cleaning robot, etc., and at-home sensing is performed by the imaging device. Furthermore, techniques for cloud processing in which an image captured at home is transferred via a network and is processed at a transfer destination have been also widely used.
In recent years, a technique called “compressed sensing” has been also developed. Compressed sensing is a technique in which a plurality of pixel values are added up and thus an image is captured, thereby compressing the image, and image reconstruction using the sparsity of the image is performed, so that image quality is maintained while the amount of data is reduced (see, for example, Toshiyuki Tanaka, “Mathematics of Compressed Sensing,” IEICE Fundamentals Review, vol. 4, no. 1, pp. 39-47, 2010). The expression “an image is sparse” herein means a phenomenon in which, when an image is projected onto a wavelet space, a discrete cosine (DCT) space, or the like, many coefficient values are substantially zero. As an image reconstruction method using the sparsity of an image, L0 norm minimization or L1 norm minimization is used in compressed sensing.
Furthermore, a solid-state image sensor has been proposed in which, a technique of compressed sensing is introduced to an image sensor, and thus, a sample and hold circuit is not necessary, and image degradation due to increase in noise, increase in area, and reduction in speed may be reduced (see, for example, Japanese Unexamined Patent Publication No. 2010-245955).
Related art is disclosed, for example, in the following documents: Japanese Unexamined Patent Publication No. 2010-245955; Toshiyuki Tanaka, “Mathematics of Compressed Sensing,” IEICE Fundamentals Review, vol. 4, no. 1, pp. 39-47, 2010; J. Ma, “Improved Iterative Curvelet Thresholding for Compressed Sensing and Measurement,” IEEE Transactions on Instrumentation and Measurement, Vol. 60, Iss. 1, pp. 126-136, 2011; Toshihide Ibaraki, Masao Fukushima, “Method of Optimization,” Information mathematics course, vol. 14, Kyoritsu Shuppan Co., Ltd., pp. 159-164, Jul. 20, 1993, First Edition/First Copy; D. Takhar, J. N. Laska, M. B. Wakin. M. F. Durate, D. Baron, S. Sarvotham, K. F. Kelly, and R. G. Baraniuk, “A New Compressive Imaging Camera Architecture using optical-domain compression,” Proc. of Computational Imaging IV at SPIE Electronic Imaging, 2006; Y. Oike and A. E. Gamal, “A 256×256 CMOS Image Sensor with ΔΣ-Based Single-Shot Compressed Sensing,” IEEE International Solid-State Circuits Conference (ISSCC) Dig. of Tech. Papers, pp. 386-387, 2012; and Makoto Nakashizuka, “Sparse Signal Representation and Its Image Processing Application,” Journal of the Institute of Image Information and Television Engineers, Vol. 65, No. 10, pp. 1381-1386.
An image captured at home is very personal. Therefore, in the above-described at-home sensing technique, high-level privacy protection is required, for example, in the following terms.
(1) Reducing the risk of a captured image being intercepted while the captured image is transmitted.
(2) Reducing the risk of captured image data left in a device being seen by someone else.
Regarding (1), in order to maintain confidentiality in communication, techniques in which an image is encrypted have been widely known, and techniques in which a public key and a secret key are used have been widely spread. On the other hand, regarding (2), for example, if original captured image data is left in a memory of a device, there is a probability that the captured image is seen or copied by someone else after the device has been disposed. In order for this not to happen, for example, a measure in which, when a device is disposed, image data therein is also discarded has to be taken, and technically, there is a still problem remaining.
It is therefore an object of the present disclosure to solve the above-described problem and to provide an imaging system that may capture a desired image such that captured image data is not left in an imaging device using a technique of compressed sensing.